Artificial Intelligence #artificial intelligence#robotics
ToolSelf AI Agents Achieve 28.8 Point Gain Through Runtime Self-Reconfiguration
Researchers propose ToolSelf, a paradigm that lets LLM-powered agents dynamically update configurations during execution. By treating reconfiguration as a tool-use action, agents adjust sub-goals, strategies, and toolboxes on the fly. The Configuration-Aware Two-stage Training (CAT) yields an average 28.8-point improvement over static baselines, rivaling task-specialized systems even in zero-shot settings.
Jun 16, 2026 1 source